Data Management in an International Data Grid Project

By Wolfgang Hoschek, J. Martínez, A. Samar, Heinz Stockinger, Kurt Stockinger. IEEE/ACM International Conference on Grid Computing, 2000

521 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Hardware and Architecture

View Paper: https://www.semanticscholar.org/paper/9001f656685fb9ba54cae24f84445af204ee3e91

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Citations in the corpus

Economic models for resource management and scheduling in Grid computing (2002, methodology): “In Data Grid environments [10], large amounts of data are distributed and replicated to several sites all around the globe.”
Economic-based Distributed Resource Management and Scheduling for Grid Computing (2002, methodology): “3 Data Grid CERN, the European Organization for Nuclear Research, and the High-Energy Physics (HEP) community have established an International Data Grid project [139] with intent to apply the work to other scientific communities such as Earth Observation and Bioinformatics.”
Secure, Efficient Data Transport and Replica Management for High-Performance Data-Intensive Computing (2001, methodology): “These include the Distributed Parallel Storage System (DPSS) and the High Performance Storage System (HPSS), which provide highperformance access to data and utilize parallel data transfer and/or striping across multiple servers to improve performance [ 1 ][2].”
Grids and Grid technologies for wide‐area distributed computing (2002, methodology): “The European DataGrid project, led by CERN, is funded by the EuropeanUnion with the aim of setting up a computational and data-intensive Grid of resources for the analysis of data coming from scientific exploration [10].”
The Grid Economy (2005, methodology): “An example of such a system would be the tier-level model proposed by the MONARC [46] group within CERN for replicating the data produced by the Large Hadron Collider (LHC) [36], [71] for use within the ATLAS and CMS collaborations.”
Data management and transfer in high-performance computational grid environments (2002, methodology): “Files are replicated in a hierarchical manner, with all files stored at a central location (CERN) and decreasing subsets of the data stored at national and regional data centers [ 4 ][5].”
A taxonomy and survey of grid resource management systems for distributed computing (2002, methodology): “For example, high energy physics applications need to process massive data generated (in the order of GB/second) by an experiment that will be using the LHC (Large Hadron Collider) from 2005 onwards [13].”
The Anatomy of the Grid: Enabling Scalable Virtual Organizations (2001, background): “• Data replication services support the management of VO storage (and perhaps also network and computing) resources to maximize data access performance with respect to metrics such as response time, reliability, and cost (Allcock et al., 2001; Hoschek et al., 2000).”